| commit | 457ab9831afc95b14ccf2a1a9397a923e3b16f8d | [log] [tgz] |
|---|---|---|
| author | Daniel Becker <daniel.becker@cloudera.com> | Wed Apr 03 23:43:51 2024 +0200 |
| committer | Daniel Becker <daniel.becker@cloudera.com> | Fri Apr 26 13:18:54 2024 +0000 |
| tree | 470ef032200c74ab9ed055b47bbff1018c44e0f7 | |
| parent | b39cd79ae84c415e0aebec2c2b4d7690d2a0cc7a [diff] |
IMPALA-12973,IMPALA-11491,IMPALA-12651: Support BINARY nested in complex types in select list
Binary fields in complex types are currently not supported at all for
regular tables (an error is returned). For Iceberg metadata tables,
IMPALA-12899 added a temporary workaround to allow queries that contain
these fields to succeed by NULLing them out. This change adds support
for displaying them with base64 encoding for both regular and Iceberg
metadata tables.
Complex types are displayed in JSON format, so simply inserting the
bytes of the binary fields is not acceptable as it would produce invalid
JSON. Base64 is a widely used encoding that allows representing
arbitrary binary information using only a limited set of ASCII
characters.
This change also adds support for top level binary columns in Iceberg
metadata tables. However, these are not base64 encoded but are returned
in raw byte format - this is consistent with how top level binary
columns from regular (non-metadata) tables are handled.
Testing:
- added test queries in iceberg-metadata-tables.test referencing both
nested and top level binary fields; also updated existing queries
- moved relevant tests (queries extracting binary fields from within
complex types) from nested-types-scanner-basic.test to a new
binary-in-complex-type.test file and also added a query that selects
the containing complex types; this new test file is run from
test_scanners.py::TestBinaryInComplexType::\
test_binary_in_complex_type
- moved negative tests in AnalyzerTest.TestUnsupportedTypes() to
AnalyzeStmtsTest.TestComplexTypesInSelectList() and converted them to
positive tests (expecting success); a negative test already in
AnalyzeStmtsTest.TestComplexTypesInSelectList() was also converted
Change-Id: I7b1d7fa332a901f05a46e0199e13fb841d2687c2
Reviewed-on: http://gerrit.cloudera.org:8080/21269
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Reviewed-by: Csaba Ringhofer <csringhofer@cloudera.com>
Lightning-fast, distributed SQL queries for petabytes of data stored in open data and table formats.
Impala is a modern, massively-distributed, massively-parallel, C++ query engine that lets you analyze, transform and combine data from a variety of data sources:
The fastest way to try out Impala is a quickstart Docker container. You can try out running queries and processing data sets in Impala on a single machine without installing dependencies. It can automatically load test data sets into Apache Kudu and Apache Parquet formats and you can start playing around with Apache Impala SQL within minutes.
To learn more about Impala as a user or administrator, or to try Impala, please visit the Impala homepage. Detailed documentation for administrators and users is available at Apache Impala documentation.
If you are interested in contributing to Impala as a developer, or learning more about Impala's internals and architecture, visit the Impala wiki.
Impala only supports Linux at the moment. Impala supports x86_64 and has experimental support for arm64 (as of Impala 4.0). Impala Requirements contains more detailed information on the minimum CPU requirements.
Impala runs on Linux systems only. The supported distros are
Other systems, e.g. SLES12, may also be supported but are not tested by the community.
This distribution uses cryptographic software and may be subject to export controls. Please refer to EXPORT_CONTROL.md for more information.
See Impala's developer documentation to get started.
Detailed build notes has some detailed information on the project layout and build.